Greyson Brothers
AI Research @ Johns Hopkins APL
- Role
- Ai Research Scientist at Johns Hopkins Applied Physics Laboratory
- Location
- Washington, DC, US
- LinkedIn followers
- 500 followers
Experience
Ai Research Scientist
Johns Hopkins Applied Physics Laboratory
May 2021 — Present · Washington, DC, US
Conducting deep reinforcement learning research for the control of autonomous systems in multi-agent environments. My work has focused on attention and memory mechanisms that enable neural networks to deal with flexible observation spaces, multi-modal data, and partial observability. I have also worked heavily on model interpretability, feature/reward engineering, and modeling & simulation:(ICML Spotlight Paper) Greyson Brothers. Robust Noise Attenuation via Adaptive Pooling of Transformer Outputs, 2025. URL https://icml.cc/virtual/2025/poster/46284Joshua McClellan, Greyson Brothers, Furong Huang, and Pratap Tokekar. PEnGUiN: Partially Equivariant Graph NeUral Networks for Sample Efficient MARL, 2025. URL https://arxiv.org/abs/25•••••15v1Greyson Brothers, Willa Mannering, Amber Tien, and John Winder. Uncovering Uncertainty in Transformer Inference, 2024. URL https://neurips.cc/virtual/2024/104082
Education
UCLA
Bachelor of Science - BS, Applied Mathematics
2016 — 2020
Harvard University Graduate School of Design
Design Discovery, Architecture
2019 — 2019
The Johns Hopkins University
Master of Science - MS, Computer Science
2022 — 2025
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